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JacobLinCool/whisper-large-v3-turbo-verbatim-1-lora

🤗 Hugging Face sourceautomatic-speech-recognitionmit3.4 GBsafetensors✓ 8 checksumsupdated today
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whisper-large-v3-turbo-verbatim-3-lora

This model is a fine-tuned version of openai/whisper-large-v3-turbo on the JacobLinCool/ami-disfluent dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1459
  • Wer: 7.7269
  • Cer: 3.2519
  • Decode Runtime: 111.0004
  • Wer Runtime: 0.0705
  • Cer Runtime: 0.0932

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 5e-05
  • train_batch_size: 4
  • eval_batch_size: 32
  • seed: 42
  • gradient_accumulation_steps: 16
  • total_train_batch_size: 64
  • optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 100
  • training_steps: 1000

Training results

Training Loss Epoch Step Validation Loss Wer Cer Decode Runtime Wer Runtime Cer Runtime
No log 0 0 2.2169 32.7209 17.9205 106.5404 0.0825 0.1203
0.1681 0.1 100 0.1998 9.9454 4.1038 108.1653 0.0730 0.0960
0.1025 0.2 200 0.1693 8.6885 3.7458 109.6779 0.0707 0.0957
0.2508 0.3 300 0.1590 8.3897 3.4931 110.3209 0.0716 0.0947
0.1446 1.088 400 0.1571 8.2626 3.4939 110.1930 0.0718 0.0951
0.1833 1.188 500 0.1505 8.0463 3.4298 110.3821 0.0709 0.0950
0.1409 1.288 600 0.1489 7.9948 3.3401 110.6880 0.0709 0.0939
0.1184 2.076 700 0.1492 7.9124 3.3181 110.6153 0.0728 0.0946
0.1737 2.176 800 0.1468 7.8128 3.2583 110.7120 0.0714 0.0947
0.1522 2.276 900 0.1462 7.7887 3.2604 110.7694 0.0710 0.0937
0.1077 3.064 1000 0.1459 7.7269 3.2519 111.0004 0.0705 0.0932

Framework versions

  • PEFT 0.14.0
  • Transformers 4.48.0
  • Pytorch 2.4.1+cu124
  • Datasets 3.2.0
  • Tokenizers 0.21.0